× Welcome to frontrun me, the premier site for visualizing Ethereum gas auctions. These gas auctions are often bids by frontrunners, arbitrageurs, and other programmatic network actors that seek to exploit inefficiencies in on-chain systems, ultimately profiting miners. On this site, we monitor these behaviors on the network in real-time as these bots compete for block priority in rapid-fire all-pay auctions*, showing users and mechanism designers the potential rent-seeking economy created by orderbook inefficiencies on-chain. Timing data is sourced from a global network of 8 nodes peered deeply with Ethereum. Read our full paper!
*Modern auctions are a special kind of all-pay auction, in which the winner of the auction pays some constant percentage of their bid; they do not pay full gas, as they do not pay for execution, but they must pay for attempted execution.

WARNING: THIS IS AN ALPHA VERSION OF THE SITE WITH PRELIMINARY DATA AND KNOWN BUGS. Use at your own risk and follow @ProjectChicago_ for announcements on release and more data being added.

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Individual Real-Time Auction Data


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Note: only auctions with a single detected "winner" (mined with 2+ log events) are displayed in this view. Other auctions may contain multiple sub-auctions, as the split is heuristic.

Gas Auction #1562 - 2018-11-25 09:55:24 to 09:55:30; Start Time 1543139724.9572265

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 11.000300000 () 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/416 2000000 0x29b234e2a63845f2c2713447c6cee8e7168910ba42cfea77ba69a2ee652a6068
0.920 80.500000001 (151.9114144986201) 0xDF4E525428eF1cd68a438f1d0E6A64f9163089F8/1417 1430000 0xc77e01594af6c2b08f46922ed28adcea0f14fd68ab8576a20393f140224d6071
1.336 80.500000001 (0.0) 0xDF4E525428eF1cd68a438f1d0E6A64f9163089F8/1418 1430000 0x97b3b42748ce80f69d3c6ef3e652d7ce06ecfdf9b7af85404c23cdc63df7bbae
1.841 11.000300000 (-151.9114144986201) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/137 2000000 0xecac243aba37c41e5a8412d31248439cc8d0da9bce5c7d93cd5f0e9d14fe2206
3.743 3.300000000 (-107.69424417669559) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/220653 104866 0xbd4b2751f4cad31e940f975ce9f900db9af815fd92d75f0d590f644876a756d3
4.457 11.000300000 (107.69424417669559) 0xC3Cd47aAbbab45EC41D9D46E159c2c0f55c47Bb7/109 2000000 0x9ab14437f2a4fd16710dbf32998222568f15d0855279baac6a0f9e29277126cb
5.042 123.000000000 (167.16335709696173) 0xCd5f8fa45E0cA0937F86006B9eE8fE1eEdEe5FC4/864 257122 0xf5c38cbcee60467ad70678bb00f01e89be8dd9e48f2c35c9300e125a27e224c3
5.171 123.000300000 (0.00024390214158275417) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/416 2000000 0x32a33b8438953cbc34c24ed4c3fae8deb1ed728623c6fbb34dfed9b38f0a9788
5.514 123.000300000 (0.0) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/137 2000000 0xed1edef7a14ee3ffa247243df32a2edaed0920a89d473b32d5bef6b3abe53b69
5.538 123.000300000 (0.0) 0xC3Cd47aAbbab45EC41D9D46E159c2c0f55c47Bb7/109 2000000 0x0462e5ab77b4c9c9ed2cabdd34fc288969abfb63bba597380587c37d591a5f42
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650441.
We would also like to thank NSF CNS-1330599, CNS-1514163, CNS-1564102, and CNS-1704615, ARL W911NF-16-1-0145, and IC3 Industry Partners.
Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.